Anshul Thakur
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
-
- Artificial Intelligence in Healthcare
Papers in
-
- Machine Learning in Healthcare 9
- Privacy-Preserving Technologies in Data 3
- Topic Modeling 2
- Domain Adaptation and Few-Shot Learning 1
-
- Artificial Intelligence in Healthcare 4
- Co-authors
- David A. Clifton (12 shared papers)Pulkit Sharma (2 shared papers)David W. Eyre (3 shared papers)Tingting Zhu (4 shared papers)Kim Branson (3 shared papers)Jenny Yang (1 shared paper)Patrick Schwab (3 shared papers)Anoop Chauhan (1 shared paper)
- Journals
- npj Digital Medicine (2 papers)IEEE Journal of Biomedical and Health Informatics (2 papers)Nature Communications (1 paper)Blood Advances (1 paper)Clinical Research in Cardiology (1 paper)
- Partner nations
- United KingdomChinaIndia
In The Last Decade
Anshul Thakur
15 papers receiving 102 citations
Peers
Comparison fields: 5 of 44
- Health Informatics 14
- Health Information Management 11
- Artificial Intelligence 51
- Signal Processing 5
- Radiology, Nuclear Medicine and Imaging 9
Countries citing papers authored by Anshul Thakur
This map shows the geographic impact of Anshul Thakur's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Anshul Thakur with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anshul Thakur more than expected).
Fields of papers citing papers by Anshul Thakur
This network shows the impact of papers produced by Anshul Thakur. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Anshul Thakur. The network helps show where Anshul Thakur may publish in the future.
Co-authors
The 25 scholars most cited alongside Anshul Thakur, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 21 | |
| 2 | 2021 | 21 | |
| 3 | 2025 | 12 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 5 | |
| 6 | 2022 | 5 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 4 | |
| 9 | 2024 | 4 | |
| 10 | 2022 | 4 | |
| 11 | 2023 | 4 | |
| 12 | 2024 | 3 | |
| 13 | 2025 | 2 | |
| 14 | 2022 | 2 | |
| 15 | 2024 | 1 | |
| 16 | 2025 | 0 | |
| 17 | 2022 | 0 | |
| 18 | 2025 | 0 | |
| 19 | 2025 | 0 |
About Anshul Thakur
Anshul Thakur is a scholar working on Artificial Intelligence, Health Information Management, Pulmonary and Respiratory Medicine, Computer Vision and Pattern Recognition and Health Informatics, having authored 19 papers that have together received 102 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (9 papers), Artificial Intelligence in Healthcare (4 papers), Privacy-Preserving Technologies in Data (3 papers), Topic Modeling (2 papers), Artificial Intelligence in Healthcare and Education (2 papers), Advanced Neural Network Applications (1 paper), Smart Systems and Machine Learning (1 paper) and Domain Adaptation and Few-Shot Learning (1 paper). The work is most often cited by research in Health Informatics (14 citations), Health Information Management (11 citations), Artificial Intelligence (51 citations), Signal Processing (5 citations) and Radiology, Nuclear Medicine and Imaging (9 citations). Anshul Thakur has collaborated with scholars based in United Kingdom, China and India. Frequent co-authors include David A. Clifton, Pulkit Sharma, David W. Eyre, Tingting Zhu, Kim Branson, Jenny Yang, Patrick Schwab, Anoop Chauhan, Andrew A. S. Soltan and David Thickett. Their work appears in journals such as npj Digital Medicine, IEEE Journal of Biomedical and Health Informatics, Nature Communications, Blood Advances and Clinical Research in Cardiology.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.